Mobile and desktop computers may be equipped with a camera such as a complementary metal oxide semiconductor (CMOS) or a charge coupled device (CCD) camera to support video applications. Such cameras typically provide only a limited Field of View (FOV) and require a user to be positioned directly in front of the computer in order to be captured by the camera and appear in the video.
The ring camera is a promising next-generation video capture device for mobile and desktop platforms. A ring camera is a multiple-camera based video capturing device that provides a larger FOV and has been used in conferencing and surveillance applications. Ring cameras may use panoramic image mosaic technology to construct high quality and resolution video from image frames captured by multiple camera modules.
Conventional global alignment approaches that employ an overlap region based panoramic image mosaic calculate homography in terms of the information of some pixels or the coordinates of some feature points appearing in an overlap region. Then, an image stitch can be done according to the homography to get the panoramic image. These homography calculation methods typically require 50% overlap between images.
Maximizing the FOV and resolution of a ring camera system for particular types of camera modules while achieving high-performance and power-efficiency, however, may require minimizing the overlap among the camera modules. When the overlap region among camera modules is minimized, it may be impossible to obtain enough pixels or feature points in the overlap region to perform robust homography calculation. As such, conventional homography calculation algorithms become unstable or unfeasible when the overlap region is very small.